An association study exploring the genetic relationship of psoriatic arthritis and obesity
Bibliographic record
Abstract
Objective: To determine if there is a genetic component causing psoriatic arthritis (PsA) patients to have higher BMIs when compared to the general population. Method: 696 obese samples were identified from a previous genetic study on obesity which were genotyped using a PsA SNP panel. 650 PsA patients who were examined for PsA related anthropometric measures were genotyped using an obesity SNP panel. An obesity panel was created using a gene prioritization method to create a 46 SNP obesity-weighted panel. Two separate quantitative trait analyses were performed to obtain the association between BMI and genotype of the subsequent panels using a linear regression model. Bonferroni correction was used to adjust for multiple comparisons. Results: Genotypes of two PsA-weighted SNPs, rs10782001 (FBXL19) and rs3131382 (HLA-B*39), showed a significant difference with BMI. Patients with the FBXL19 variant had an average BMI in the presence of GG genotype of 37.2 kg/m² vs 34.3 kg/m² for the AA genotype (p=0.0007). Patients with the HLA-B*39:05 variant had an average BMI with the TT genotype of 47.1 kg/m2 vs 35.4 kg/m² for the CC genotype (p=0.00005). One obesity-weighted SNP, rs11915371 (SAMMSON/FOXP1), showed a significant difference of BMI between genotypes in PsA patients. The average BMI of those with the CC genotype was 32.42 kg/m² compared to an average BMI of 29.77 kg/m² with the TT genotype (p=0.0009). Conclusion: Homozygotes for the minor allele of SNPs within HLA-B*39, FBXL19, and SAMMSON/FOXP1 have shown to have an increased BMI, suggesting a potential genetic link between these genes and PsA and obesity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".